import pandas as pd
import geopandas as gpd
import folium
import folium.plugins
import os
file_path = 'statistical-gis-boundaries-london/ESRI/London_Borough_Excluding_MHW.shp'
map_df = gpd.read_file(file_path)
df =pd.read_excel('All dataset.xlsx')
m = folium.Map(location = [51.5074, 0.1278], zoom_start = 10)
folium.Choropleth(
geo_data = map_df,
name = 'Household Income',
data = df,
columns = ['NAME','Median Household Income 2019 (annual)'],
key_on='feature.properties.NAME',
fill_color='Reds',
fill_opacity=0.7,
line_opacity=0.5,
bins=6,
nan_fill_color='White',
nan_fill_opacity=0.8,
legend_name='Income',
overlay=True,
show=False
).add_to(m)
<folium.features.Choropleth at 0x7fd74b0bac40>
folium.Choropleth(
geo_data = map_df,
name = 'Suicide Rates',
data = df,
columns = ['NAME','Suicide Rates (2019) (in %)'],
key_on='feature.properties.NAME',
fill_color='Purples',
fill_opacity=0.7,
line_opacity=0.5,
bins=6,
nan_fill_color='White',
nan_fill_opacity=0.8,
legend_name='Suicide Rates',
overlay=True,
show=False
).add_to(m)
<folium.features.Choropleth at 0x7fd74b0ba9d0>
folium.LayerControl(collapsed=False).add_to(m)
<folium.map.LayerControl at 0x7fd74b0ba0d0>
mnames=folium.GeoJson(
data=map_df,
name="Map of London Boroughs",
style_function = lambda feature: dict(fillColor= '#00000000', color= '#00000000', weight=0, opacity=-1000),
overlay=True,
control=False,
show=True,
tooltip=folium.features.GeoJsonTooltip(
fields=['NAME'],
labels=False)
).add_to(m)
m.keep_in_front(mnames)
m
m.save("map.html")